Identifying cancer hazards is the first step towards cancer prevention. The International Agency for Research on Cancer (IARC) Monographs Programme, which has evaluated nearly 1,000 agents for their carcinogenic potential since 1971, typically selects agents for hazard identification on the basis of public nominations, expert advice, published data on carcinogenicity, and public health importance.

Objectives:

Here, we present a novel and complementary strategy for identifying agents for hazard evaluation using chemoinformatics, database integration, and automated text mining.

Discussion:

To inform selection among a broad range of pesticides nominated for evaluation, we identified and screened nearly 6,000 relevant chemical structures, after which we systematically compiled information on 980 pesticides, creating network maps that allowed cluster visualization by chemical similarity, pesticide class, and publicly available information concerning cancer epidemiology, cancer bioassays, and carcinogenic mechanisms. For the IARC Monograph meetings that took place in March and June 2015, this approach supported high-priority evaluation of glyphosate, malathion, parathion, tetrachlorvinphos, diazinon, p,p′-dichlorodiphenyltrichloroethane (DDT), lindane, and 2,4-dichlorophenoxyacetic acid (2,4-D).

Conclusions:

This systematic approach, accounting for chemical similarity and overlaying multiple data sources, can be used by risk assessors as well as by researchers to systematize, inform, and increase efficiency in selecting and prioritizing agents for hazard identification, risk assessment, regulation, or further investigation. This approach could be extended to an array of outcomes and agents, including occupational carcinogens, drugs, and foods.

There is an increased need to develop novel alternative approaches to the two-year rodent bioassay for the carcinogenicity assessment of substances where the rodent bioassay is still a basic requirement, as well as for those substances where animal use is banned or limited or where information gaps are identified within legislation. The current progress in this area was addressed in a EURL ECVAM- ESTIV workshop held in October 2016, in Juan les Pins. A number of initiatives were presented and discussed, including data-driven, technology-driven and pathway-driven approaches. Despite a seemingly diverse range of strategic developments, commonalities are emerging. For example, providing insight into carcinogenicity mechanisms is becoming an increasingly appreciated aspect of hazard assessment and is suggested to be the best strategy to drive new developments. Thus, now more than ever, there is a need to combine and focus efforts towards the integration of available information between sectors. Such cross-sectorial harmonisation will aid in building confidence in new approach methods leading to increased implementation and thus a decreased necessity for the two-year rodent bioassay.

There is a growing need for quantitative approaches to extrapolate relationships between chemical exposures and early biological perturbations from animals to humans given increasing use of biological assays to evaluate toxicity pathways. We have developed such an approach using polychlorinated biphenyls (PCBs) and thyroid hormone (TH) disruption as a case study. We reviewed and identified experimental animal literature from which we developed a low-dose, linear model of PCB body burdens and decrements in free thyroxine (FT(4)) and total thyroxine (TT(4)), accounting for 33 PCB congeners; extrapolated the dose-response from animals to humans; and compared the animal dose-response to the dose-response of PCB body burdens and TH changes from eleven human epidemiological studies. We estimated a range of potencies for PCB congeners (over 4 orders of magnitude), with the strongest for PCB 126. Our approach to developing toxic equivalency models produced relative potencies similar to the toxicity equivalency factors (TEFs) from the World Health Organization (WHO). We generally found that the dose-response extrapolated from the animal studies tends to under-predict the dose-response estimated from human epidemiological studies. A quantitative approach to evaluating the relationship between chemical exposures and TH perturbations, based on animal data can be used to assess human health consequences of thyroid toxicity and inform decision-making.

BACKGROUND:Benchmark dose (BMD) modeling computes the dose associated with a prespecified response level. While offering advantages over traditional points of departure (PODs), such as no-observed-adverse-effect-levels (NOAELs), BMD methods have lacked consistency and transparency in application, interpretation, and reporting in human health assessments of chemicals. OBJECTIVES:We aimed to apply a standardized process for conducting BMD modeling to reduce inconsistencies in model fitting and selection. METHODS:We evaluated 880 dose-response data sets for 352 environmental chemicals with existing human health assessments. We calculated benchmark doses and their lower limits [10% extra risk, or change in the mean equal to 1 SD (BMD/L10/1SD)] for each chemical in a standardized way with prespecified criteria for model fit acceptance. We identified study design features associated with acceptable model fits. RESULTS:We derived values for 255 (72%) of the chemicals. Batch-calculated BMD/L10/1SD values were significantly and highly correlated (R2 of 0.95 and 0.83, respectively, n = 42) with PODs previously used in human health assessments, with values similar to reported NOAELs. Specifically, the median ratio of BMDs10/1SD:NOAELs was 1.96, and the median ratio of BMDLs10/1SD:NOAELs was 0.89. We also observed a significant trend of increasing model viability with increasing number of dose groups. CONCLUSIONS:BMD/L10/1SD values can be calculated in a standardized way for use in health assessments on a large number of chemicals and critical effects. This facilitates the exploration of health effects across multiple studies of a given chemical or, when chemicals need to be compared, providing greater transparency and efficiency than current approaches.

BACKGROUND:The issue of endocrine disrupting chemicals (EDCs) is receiving wide attention from both the scientific and regulatory communities. Recent analyses of the EDC literature have been criticized for failing to use transparent and objective approaches to draw conclusions about the strength of evidence linking EDC exposures to adverse health or environmental outcomes. Systematic review methodologies are ideal for addressing this issue as they provide transparent and consistent approaches to study selection and evaluation. Objective methods are needed for integrating the multiple streams of evidence (epidemiology, wildlife, laboratory animal, in vitro, and in silico data) that are relevant in assessing EDCs. METHODS:We have developed a framework for the systematic review and integrated assessment (SYRINA) of EDC studies. The framework was designed for use with the International Program on Chemical Safety (IPCS) and World Health Organization (WHO) definition of an EDC, which requires appraisal of evidence regarding 1) association between exposure and an adverse effect, 2) association between exposure and endocrine disrupting activity, and 3) a plausible link between the adverse effect and the endocrine disrupting activity. RESULTS:Building from existing methodologies for evaluating and synthesizing evidence, the SYRINA framework includes seven steps: 1) Formulate the problem; 2) Develop the review protocol; 3) Identify relevant evidence; 4) Evaluate evidence from individual studies; 5) Summarize and evaluate each stream of evidence; 6) Integrate evidence across all streams; 7) Draw conclusions, make recommendations, and evaluate uncertainties. The proposed method is tailored to the IPCS/WHO definition of an EDC but offers flexibility for use in the context of other definitions of EDCs. CONCLUSIONS:When using the SYRINA framework, the overall objective is to provide the evidence base needed to support decision making, including any action to avoid/minimise potential adverse effects of exposures. This framework allows for the evaluation and synthesis of evidence from multiple evidence streams. Finally, a decision regarding regulatory action is not only dependent on the strength of evidence, but also the consequences of action/inaction, e.g. limited or weak evidence may be sufficient to justify action if consequences are serious or irreversible.

Endocrine-disrupting chemicals (EDCs) are exogenous chemicals that interfere with hormone action, thereby increasing the risk of adverse health outcomes, including cancer, reproductive impairment, cognitive deficits and obesity. A complex literature of mechanistic studies provides evidence on the hazards of EDC exposure, yet there is no widely accepted systematic method to integrate these data to help identify EDC hazards. Inspired by work to improve hazard identification of carcinogens using key characteristics (KCs), we have developed ten KCs of EDCs based on our knowledge of hormone actions and EDC effects. In this Expert Consensus Statement, we describe the logic by which these KCs are identified and the assays that could be used to assess several of these KCs. We reflect on how these ten KCs can be used to identify, organize and utilize mechanistic data when evaluating chemicals as EDCs, and we use diethylstilbestrol, bisphenol A and perchlorate as examples to illustrate this approach.

Humans are frequently exposed to acrylamide, a probable human carcinogen found in commonplace sources such as most heated starchy foods or tobacco smoke. Prior evidence has shown that acrylamide causes cancer in rodents, yet epidemiological studies conducted to date are limited and, thus far, have yielded inconclusive data on association of human cancers with acrylamide exposure. In this study, we experimentally identify a novel and unique mutational signature imprinted by acrylamide through the effects of its reactive metabolite glycidamide. We next show that the glycidamide mutational signature is found in a full one-third of approximately 1600 tumor genomes corresponding to 19 human tumor types from 14 organs. The highest enrichment of the glycidamide signature was observed in the cancers of the lung (88% of the interrogated tumors), liver (73%), kidney (>70%), bile duct (57%), cervix (50%), and, to a lesser extent, additional cancer types. Overall, our study reveals an unexpectedly extensive contribution of acrylamide-associated mutagenesis to human cancers.

Assessing adverse effects from environmental chemical exposure is integral to public health policies. Toxicology assays identifying early biological changes from chemical exposure are increasing our ability to evaluate links between early biological disturbances and subsequent overt downstream effects. A workshop was held to consider how the resulting data inform consideration of an "adverse effect" in the context of hazard identification and risk assessment.Our objective here is to review what is known about the relationships between chemical exposure, early biological effects (upstream events), and later overt effects (downstream events) through three case studies (thyroid hormone disruption, antiandrogen effects, immune system disruption) and to consider how to evaluate hazard and risk when early biological effect data are available.Each case study presents data on the toxicity pathways linking early biological perturbations with downstream overt effects. Case studies also emphasize several factors that can influence risk of overt disease as a result from early biological perturbations, including background chemical exposures, underlying individual biological processes, and disease susceptibility. Certain effects resulting from exposure during periods of sensitivity may be irreversible. A chemical can act through multiple modes of action, resulting in similar or different overt effects.For certain classes of early perturbations, sufficient information on the disease process is known, so hazard and quantitative risk assessment can proceed using information on upstream biological perturbations. Upstream data will support improved approaches for considering developmental stage, background exposures, disease status, and other factors important to assessing hazard and risk for the whole population.